What are the responsibilities and job description for the Senior Data Scientist with Generative AI Experience position at CBC?
Hiring: Senior LLM Data Scientist with Strong Generative AI Experience
We have an exciting opportunity with our client for a Senior LLM Data Scientist with strong expertise in Generative AI. The ideal candidate should meet the following requirements:
Responsibilities & Requirements:
1. 3 years of experience in R/Python, Linux, Spark on AWS cloud, or algorithmic design in Python/C#/C .
2. Proficiency with Amazon AWS Sagemaker, Jupyter Notebook, Python Scikit-learn, TensorFlow.
3. Experience in building Vector DB, NLP, LLM, and GenAI tools (LoRA, LangChain, RAG, LLM Fine-Tuning, PEFT preferred).
4. Strong skills in SQL and relational databases (Oracle, PostgreSQL, MySQL, RDS, Redshift, Hadoop EMR, Hive).
5. Experience in data processing, cleansing, and normalization.
6. Solid understanding of machine learning techniques (NLP, BERT, RoBERTa, GPT, LLMs).
7. Familiarity with code repositories and deployment pipelines (Jenkins, Git).
8. Experience with big data processing (Hadoop, Spark) and data streaming (Kafka, RabbitMQ, NiFi, Kinesis).
9. Knowledge of data visualization tools (Tableau, Kibana, Quicksights).
10. Ability to handle large datasets and extract meaningful insights.
11. Comfortable working with ambiguity (imperfect data, loosely defined concepts).
12. 3 years of experience in machine learning or deep learning models/systems.
13. Strong scripting (Shell, SQL) and coding skills (Python, Scala).
14. 1 year of experience in deep learning (CNN, RNN, LSTM).
15. Knowledge of machine learning models (regression, classification, clustering, graph models).
Qualifications & Requirements:
MS in Computer Science, Statistics, Mathematics, Engineering, or a related field (PhD preferred).
Preferred Qualifications:
1. Experience with deep learning frameworks (MXNet, TensorFlow, Keras, Caffe, PyTorch, Theano).
2. Experience with search architecture (Solr, ElasticSearch).
3. Knowledge of ontologies (Zeno, OWL, RDF, SPARQL).
4. Experience with NLP techniques (LDA, TF/IDF, Sentiment Analysis) and technologies (Python NLTK, Spacy).
5. Knowledge of microservices, service mesh, API development, and test automation.
6. Experience with Docker, Kubernetes, and container frameworks.
7. Experience in developing new computational linguistics and NLP techniques.
If you or someone you know is a good fit for this role, please share suitable profiles with us at bharathiraja.m@cloudbclabs.com